Skip to main content

[BETA] Google AI Studio (Gemini) Files API

Use this to upload files to Google AI Studio (Gemini).

Useful to pass in large media files to Gemini's /generateContent endpoint.

ActionSupported
createYes
deleteNo
retrieveNo
listNo

Usage​

import base64
import requests
from litellm import completion, create_file
import os


### UPLOAD FILE ### 

# Fetch the audio file and convert it to a base64 encoded string
url = "https://cdn.openai.com/API/docs/audio/alloy.wav"
response = requests.get(url)
response.raise_for_status()
wav_data = response.content
encoded_string = base64.b64encode(wav_data).decode('utf-8')


file = create_file(
    file=wav_data,
    purpose="user_data",
    extra_headers={"custom-llm-provider": "gemini"},
    api_key=os.getenv("GEMINI_API_KEY"),
)

print(f"file: {file}")

assert file is not None


### GENERATE CONTENT ### 
completion = completion(
    model="gemini-2.0-flash",
    messages=[
        {
            "role": "user",
            "content": [
                { 
                    "type": "text",
                    "text": "What is in this recording?"
                },
                {
                    "type": "file",
                    "file": {
                        "file_id": file.id,
                        "filename": "my-test-name",
                        "format": "audio/wav"
                    }
                }
            ]
        },
    ]
)

print(completion.choices[0].message)

Azure Blob Storage Integration​

LiteLLM supports using Azure Blob Storage as a target storage backend for Gemini file uploads. This allows you to store files in Azure Data Lake Storage Gen2 instead of Google's managed storage.

Step 1: Setup Azure Blob Storage​

Configure your Azure Blob Storage account by setting the following environment variables:

Required Environment Variables:

  • AZURE_STORAGE_ACCOUNT_NAME - Your Azure Storage account name
  • AZURE_STORAGE_FILE_SYSTEM - The container/filesystem name where files will be stored
  • AZURE_STORAGE_ACCOUNT_KEY - Your account key

Step 2: Pass Azure Blob Storage as Target Storage​

When uploading files, specify target_storage: "azure_storage" to use Azure Blob Storage instead of the default storage.

Supported File Types:

Azure Blob Storage supports all Gemini-compatible file types:

  • Images: PNG, JPEG, WEBP
  • Audio: AAC, FLAC, MP3, MPA, MPEG, MPGA, OPUS, PCM, WAV, WEBM
  • Video: FLV, MOV, MPEG, MPEGPS, MPG, MP4, WEBM, WMV, 3GPP
  • Documents: PDF, TXT

Note: Only small files can be sent as inline data because the total request size limit is 20 MB.

Step 3: Upload Files with Azure Blob Storage for Gemini​

  1. Setup config.yaml
model_list:
    - model_name: "gemini-2.5-flash"
      litellm_params:
        model: gemini/gemini-2.5-flash
        api_key: os.environ/GEMINI_API_KEY
  1. Set environment variables
export AZURE_STORAGE_ACCOUNT_NAME="your-storage-account"
export AZURE_STORAGE_FILE_SYSTEM="your-container-name"
export AZURE_STORAGE_ACCOUNT_KEY="your-account-key"

or add them in your .env

  1. Start proxy
litellm --config config.yaml
  1. Upload file with Azure Blob Storage
from openai import OpenAI

client = OpenAI(
    base_url="http://0.0.0.0:4000",
    api_key="sk-1234"
)

# Upload file to Azure Blob Storage
file = client.files.create(
    file=open("document.pdf", "rb"),
    purpose="user_data",
    extra_body={
        "target_model_names": "gemini-2.0-flash",
        "target_storage": "azure_storage"  # 👈 Use Azure Blob Storage
    }
)

print(f"File uploaded to Azure Blob Storage: {file.id}")

# Use the file with Gemini
completion = client.chat.completions.create(
    model="gemini-2.0-flash",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Summarize this document"},
                {
                    "type": "file",
                    "file": {
                        "file_id": file.id,
                    }
                }
            ]
        }
    ]
)

print(completion.choices[0].message.content)
info

Files uploaded to Azure Blob Storage are stored in your Azure account and can be accessed via the returned file ID. The file URL format is: https://{account}.blob.core.windows.net/{container}/{path}